Publications by authors named "Q Al-Balas"

This study aimed to identify novel Glyoxalase-I (Glo-I) inhibitors with potential anticancer properties, focusing on anthraquinone amide-based derivatives. We synthesized a series of these derivatives and conducted in silico docking studies to predict their binding interactions with Glo-I. In vitro assessments were performed to evaluate the anti-Glo-I activity of the synthesized compounds.

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Background: Glyoxalase system detoxifies methylglyoxal and other ketoaldehydes to produce innocuous metabolites that allow the cells to function normally. Its inhibition in cancer cells causes these toxic metabolites to accumulate, and the cancer cells enter the apoptotic stage.

Methods: The techniques of Computer-Aided Drug Design (CADD) were used, and the compounds possessing a zinc-binding group from commercial databases were extracted, using the pharmacophore search protocol.

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In this study, a fragment-based drug design approach, particularly drug design, was implemented utilising three different crystal structures in order to discover new privileged scaffolds against glyoxalase-I enzyme as anticancer agents. The fragments were evoluted to indicate potential inhibitors with high receptor affinities. The resulting compounds were served as a benchmark for choosing similar compounds from the ASINEX® database by applying different computational ligand-based drug design techniques.

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In recent years, the genetic testing and selection of IVF embryos, known as preimplantation genetic testing (PGT), has gained much traction in clinical assisted reproduction for preventing transmission of genetic defects. However, a more recent ethically and morally controversial development in PGT is its possible use in selecting IVF embryos for optimal intelligence quotient (IQ) and other non-disease-related socially desirable traits, such as tallness, fair complexion, athletic ability, and eye and hair colour, based on polygenic risk scores (PRS), in what is referred to as PGT-P. Artificial intelligence (AI) and machine learning-based analysis of big data sets collated from genome sequencing of specific human ethnic populations can be used to estimate an individual embryo's likelihood of developing such multifactorial traits by analysing the combination of specific genetic variants within its genome.

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Background: Defensive medicine (DM) is a deviation from medical practice that is induced primarily by a threat of liability. While the DM behavior is well studied in the developed countries, little is known in developing countries and never been evaluated in Jordan.

Objective: To evaluate the prevalence of DM practice in Jordan among physicians and to investigate reasons behind its practice and potential strategies to alleviate this practice.

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